Results revealed that post-alcohol administration, the VAR + L-NTX group had significantly reduced craving for cigarettes over and above all other medication groups . The VAR + L-NTX group also demonstrated reduced alcohol “high” compared to placebo or monotherapy medication groups . Results post-cigarette administration revealed that the VAR + L-NTX group had reduced cigarette craving in comparison to placebo . The VAR + L-NTX group also exhibited lower cigarette “high” feelings than placebo and L-NTX groups . Examination of self-report alcohol and cigarette use on the 9-day medication titration period revealed that the VAR + L-NTX group and L-NTX group were associated with fewer drinks per drinking day than placebo alone . For cigarette use, participants in the VAR + L- NTX group had significantly fewer cigarettes per smoking day than L-NTX and placebo groups . Furthermore, a subset of participants completed a neuroimaging session to examine brain responses to visual smoking related versus neutral cues . Results indicated significant differences in brain activation during cigarette cues for the active medication groups compared to placebo. In comparison to placebo and L-NTX groups, the VAR+NTX group displayed reduce activation of the bilateral anterior cingulate cortex . Interestingly, all medications reduced left NAcc activity compared to placebo suggesting that medications alone or in combination exert reductions neural signals that are associated with appetitive behavior . Lastly, in this study, participants smoked the cigarette following alcohol consumption with the use of a smoking topography device,cannabis grow table allowing for examination of the nuanced manner in which individuals smoke a cigarette .
Results revealed that the VAR + L-NTX group altered smoking topography resulting in a pattern of less intense puffing behavior. Specifically, active medication groups had suppressed puff duration and velocity slopes over the course of the single cigarette in comparison to placebo. The VAR + L-NTX group also had lower average inter-puff interval than L-NTX and NTX groups, as well as lower average puff volume compared to all other groups . Collectively, these results provide initial evidence for the potential of the combination of varenicline and naltrexone to serve a possible efficacious pharmacotherapy option for heavy drinking smokers. The aforementioned findings from human laboratory studies set the stage for a randomized clinical trial conducted by the Ray Lab between 2015-2019. This randomized clinical trial was funded by the National Institute on Drug Abuse R01 . To date, this RCT was the first clinical trial to date to examine the combination of VAR and NTX in heavy drinking smokers for smoking cessation. This study was a double-blind, randomized clinical trial comparing varenicline alone plus placebo versus the combination of varenicline plus naltrexone for smoking cessation in a sample of heavy-drinking daily smokers who want to quit smoking. Data from this study was used for Chapter 2 and Chapter 3 of the dissertation. Participants were recruited from the Los Angeles community through a variety of print and online advertisements . Men and women of all ethnic backgrounds were recruited into the study. Advertisements were targeted to heavy drinking smokers interested in quitting smoking and reducing their drinking. During the screening session, interested individuals called the lab and were provided information about the study, and completed an initial telephone screen for inclusion and exclusion criteria following verbal consent. Those who met the study criteria as ascertained during the phone interview were asked to come to the laboratory to provide informed consent.
After consenting, subjects were asked to provide a urine sample for cotinine verification of smoking status and complete a series of smoking and individual differences measures . Eligible participants then completed the screening physical exam. Those who passed the physical exam were urn randomized to one of the two medication conditions. Urn randomization was also used to balance the medication groups by gender, number of cigarettes per day, and drinks per drinking day. Despite declining rates of cigarette use , co-use between alcohol and cigarettes remains high. Recent estimates from the National Epidemiological Survey on Alcohol and Related Conditions revealed the odds of having a past 12-months Diagnostic and Statistical Manual-5 nicotine use disorder is 3.2 times higher in the presence of an alcohol use disorder , regardless of AUD severity . Co-use between alcohol and cigarettes has been associated with an increased risk of head and neck cancers, , as well as mood disorders . The negative impact of this co-use pattern extends to cessation attempts, such that daily smokers with a current or past AUD are less likely to quit smoking and cigarette smoking has been linked with an increased risk of relapse to AUDs . Multiple underlying mechanisms of action have been proposed to explain this robust bi-directional relationship. Genetic studies have highlighted the role of the human gene cluster CHRNA5/A3/B4 in both alcohol and nicotine use . Pre-clinical and behavioral pharmacology studies have also highlighted varenicline reducing alcohol consumption and in improving smoking cessation outcomes . Taken together, the epidemiological rates of co-use, its impact on treatment outcomes, and mechanisms underlying this co-use suggests that heavy drinking smokers constitute a unique subpopulation of substance users. Towards elucidating mechanisms of co-use, heavy drinking smokers can be examined through the application of behavioral economics, which combines principles of economics and psychology to further our understanding choice behavior .
The contemporary application of behavioral economics to addictive behavior is referred to as the reinforcer pathology approach, which emphasizes persistently high reinforcing value of a drug, disproportionate immediate preference for that reward despite long-term consequences, and a paucity of alternative reinforcers . Demand curve analyses can be used to operationalize the relative reinforcing efficacy of a substance by examining relationship between consumption of a substance and price . Hypothetical purchase tasks, in which individuals report how much of a specific substance they would consume at increasing prices, can be used to generate a demand curve. Various indices from the demand curve reflect relative reinforcing efficacy, which has been proposed to be a heterogeneous phenomenon , can be analyzed including intensity , Omax , Pmax , Breakpoint , and Elasticity . Various indices of demand assessed via hypothetical purchase task have been associated with real-world alcohol use. In a college sample, all five indices of demand have demonstrated significant correlations with self-report drinks per week and heavy drinking episodes per week , Intensity of demand, as well as craving for alcohol, have been associated with a greater number of AUD symptoms . Indices of demand have also been examined as predictors for treatment outcomes. Following a brief alcohol intervention, greater maximum expenditure for alcohol and first price suppressing consumption to zero have been demonstrated to predict greater drinking at 6-month post-intervention follow up . In the realm of tobacco use, a recent meta-analysis found all five behavioral economic indices to be strongly associated with cigarette consumption and tobacco dependence, with intensity, Omax,cannabis drying trays and elasticity displaying the most robust associations highlighting the robust associations between cigarette demand and cigarette use . Even among cannabis use, demand for cannabis has been shown to predict cannabis use frequency and quantity . Collectively, these results demonstrate how behavioral economic indices are implicated in both alcohol and tobacco dependence. However, when taking these findings together, few studies to date have examined behavioral economic indices of alcohol in a sample of heavy drinking smokers. One previous study has found that heavy drinking smokers, relative to heavy drinking nonsmokers, report greater alcohol Omax and break point . An additional study with college students who reported at least one heavy drinking episode in the past month found that the same pattern of higher alcohol Omax and Break point with those who also reported smoking at least one cigarette in the past month in comparison to non-smokers, as well as greater Pmax .
Amlung and colleagues proposed that it is not entirely clear whether heavy drinking smokers are more sensitive to alcohol reward specifically, or if they demonstrate a generalized hypersensitivity to reward and/or multiple drugs. Thus, further research is needed to elucidate how demand for cigarettes and alcohol may be altered and influence each other in a sample that uses both substances. Previously, the latent structure of demand curve indices has been found to have two components, Amplitude and Persistence, with Omax loading on both, Intensity loading on the former and Pmax, Elasticity, and Break point loading on the latter . Persistence reflects measures of sensitivity to increase price whereas Amplitude reflects the amount consumed and spent. In examining these two factors in relation to self-reported alcohol use and alcohol problems, Persistence has been suggested to reflect a more compulsive dimension of alcohol-seeking thus being more relevant to alcohol-dependent individuals . Amplitude has been suggested to be more salient among heavy drinkers as it is closely related to current alcohol use measures. These two-factors extend the initial five facets of demand to represent the underlying relationship among these demand indices. Using these two factors as opposed to the five demand indices may aid in reducing Type I error inflation . To our knowledge, no study to date has examined alcohol and cigarette demand, via hypothetical purchase tasks, in a clinical sample of heavy drinking smokers. The aims of the present study are: 1) examine the association between latent factors of demand and demand indices for nicotine and alcohol in a sample of heavy drinking smokers, 2) examine the association between nicotine and alcohol use severity and latent factors of demand and demand indices for nicotine and alcohol respectively, and 3) test cross-substance associations between alcohol and cigarette use severity/past 30 day use and latent factors of demand and demand indices. Based on the small existing literature, we hypothesize heavy alcohol use will be associated with increased demand for cigarettes and heavier smoking will predict increased demand for alcohol. Participants consisted of a community sample of non-treatment seeking daily smokers who drank heavily recruited from the greater Los Angeles area. Data for this study were collected at the initial eligibility screening visit and prior to medication assignment as part of a larger study medication study examining varenicline and naltrexone .Interested participants completed a phone interview to determine eligibility. Eligible participants were non-treatment seeking daily smokers who were also heavy drinkers, consistent with the National Institute on Alcohol Abuse and Alcoholism guidelines of ≥14 drinks/week for men and ≥7 for women at least monthly over the prior year. If eligible following the telephone interview, participants were invited for an in-person screening visit. Participants were required to have a breath alcohol concentration of 0.000 g/dl and were excluded if they tested positive for any drugs, with the exception marijuana. Prior to the primary analyses for the APT and CPT, invariant responding and excessive preference reversals across the task were identified and removed from the analysis. Participants with missing data for intensity were excluded from all analyses. A total of 461 participants completed the initial screening. Forthe APT, 111 were removed at the initial data processing stage due to missing data , missing data for intensity , and an intensity value close to zero implying lack of understanding of the task . At the effort check stage, 28 were removed due to excessive preference reversals and invariant responding . For the CPT, 101 were removed at the initial data processing stage due to missing data and intensity values equal to zero implying lack of understanding of the task . At the effort check stage, 28 were removed due to excessive preference reversals and invariant responding . One additional participant was excluded due to having a majority of outlying values. Due to purchase task data processing steps the final sample sizes for the alcohol and cigarette purchase task indices differ. Specifically, not all participants who had data present for the alcohol purchase task also had data present for the cigarette purchase task. A total of 383 participants had valid purchase task data, with 322 for the APT and 334 for the CPT. A total of 273 participants had valid data present for both the APT and CPT. Outliers at the price level and at the index level were winsorized to the exact next highest non-outlying value . For the APT, the percentage of outlying responses at the item-level ranged from .6% – 1.9%. The percentage of index-level outliers ranged from .3% – 6.8%. For the CPT, the percentage of outlying responses at the item-level ranged from .6% – 3.0%. The percentage of index-level outliers ranged from .9% – 3.0%.